Groundwater vulnerability assessment and evaluation of human activity impact (HAI) within the Dead Sea groundwater basin,Jordan

Groundwater vulnerability to contamination was determined within the Dead Sea groundwater basin, Jordan, using the DRASTIC model and evaluation of human activity impact (HAI). DRASTIC is an index model composed of several hydrogeological parameters and, in this study, the recharge parameter component was calculated as a function of rainfall, soil permeability, slope percentage, fault system, and the intersection locations between the fault system and the drainage system, based on the hydrogeologic characteristics of hard-rock terrain in an arid region. To evaluate the HAI index, a land use/cover map was produced using an ASTER VNIR image, acquired for September 2004, and combined with the resultant DRASTIC model. By comparing the DRASTIC and HAI indices, it is found that human activity is affecting the groundwater quality and increasing its pollution risk. The land use/cover map was verified using the average nitrate concentrations in groundwater associated with land in each class. A sensitivity analysis was carried out in order to study the model sensitivity. The analyses showed that the depth to water table and hydraulic conductivity parameters have no significant impact on the model, whereas the impact of vadose zone, aquifer media, and recharge parameters have a significant impact on the DRASTIC model.     

Pedodiversity and pedogenesis in Zayandeh-rud Valley, Central Iran

A geomorphic hierarchical downscaling method was used to decompose the forms and processes forming the landscapes and their subdivisions in the main region of Zayandeh-rud Valley. The purpose of this study was to determine the degree of soil heterogeneity and to check if K-entropy would be a good measure of soil evolution. Soil diversity analyses were performed considering soil families as individuals of soil entities in each geomorphic or taxonomic category level. Pedodiversity indices were used to follow the trend of soil and landscape evolution. The relationships between K-entropy (Shannon diversity index) and pedo-richness versus increasing area were analyzed to find out the effects of soil–landscape evolution on complexity of soil patterns in different geomorphic surfaces. Entropy–age relationship was studied to check the pedogenetic pathways responsible for soil landscape evolution. The soil diversity increases as geomorphic and taxonomic hierarchy levels decrease. The diversity indices were high when the sequence of soil horizons in a homogeneous family was also investigated. An increase in K-entropy of soil and landscape during time confirms the hypothesis of soil divergence evolution, whereby differences in initial conditions or local perturbations, and dynamic instability appear to have produced more variable soils and landscapes in the study area.     

Dynamics of energy sector and GHG emissions in Saudi Arabia

The energy sector is the main contributor to GHG emissions in Saudi Arabia. The tremendous growth of GHG emissions poses serious challenges for the Kingdom in terms of their reduction targets, and also the mitigation of the associated climate changes. The rising trend of population and urbanization affects the energy demand, which results in a faster rate of increase in GHG emissions. The major energy sector sources that contribute to GHG emissions include the electricity generation, road transport, desalination plants, petroleum refining, petrochemical, cement, iron and steel, and fertilizer industries. In recent years, the energy sector has become the major source, accounting for more than 90% of national CO₂ emissions. Although a substantial amount of research has been conducted on renewable energy resources, a sustainable shift from petroleum resources is yet to be achieved. Public awareness, access to energy-efficient technology, and the development and implementation of a legislative framework, energy pricing policies, and renewable and alternative energy policies are not mature enough to ensure a significant reduction in GHG emissions from the energy sector. An innovative and integrated solution that best serves the Kingdom's long-term needs and exploits potential indigenous, renewable, and alternative energy resources while maintaining its sustainable development stride is essential.

Policy relevance

The main contributor to GHG emissions in Saudi Arabia is the energy sector that accounts for more than 90% of the national CO₂ emissions. Tremendous growth of GHG emissions poses serious challenges for the Kingdom in their reduction and mitigating the associated climate changes. This study examines the changing patterns of different activities associated with energy sector, the pertinent challenges, and the opportunities that promise reduction of GHG emissions while providing national energy and economic security. The importance of achieving timely, sustained, and increasing reductions in GHG emissions means that a combination of policies may be needed. This study points to the long-term importance of making near- and medium-term policy choices on a well-informed, strategic basis. This analytical paper is expected to provide useful information to the national policy makers and other decision makers. It may also contribute to the GHG emission inventories and the climate change negotiations.     

Correction: Impact of excessive groundwater pumping on rejuvenation processes in the Bandung basin (Indonesia) as determined by hydrogeochemistry and modeling

In the Bandung basin, Indonesia, excessive groundwater pumping caused by rapid increases in industrialization and population growth has caused subsurface environmental problems, such as excessive groundwater drawdown and land subsidence. In this study, multiple hydrogeochemical techniques and numerical modeling have been applied to evaluate the recharge processes and groundwater age (rejuvenation). Although all the groundwater in the Bandung basin is recharged at the same elevation at the periphery of the basin, the water type and residence time of the shallow and deep groundwater could be clearly differentiated. However, there was significant groundwater drawdown in all the depression areas and there is evidence of groundwater mixing between the shallow and deep groundwater. The groundwater mixing was traced from the high dichlorodifluoromethane (CFC-12) concentrations in some deep groundwater samples and by estimating the rejuvenation ratio (R) in some representative observation wells. The magnitude of CFC-12 concentration, as an indicator of young groundwater, showed a good correlation with R, determined using ¹⁴C activity in samples taken between 2008 and 2012. These correlations were confirmed with the estimation of vertical downward flux from shallower to deeper aquifers using numerical modeling. Furthermore, the change in vertical flux is affected by the change in groundwater pumping. Since the 1970s, the vertical flux increased significantly and reached approximately 15% of the total pumping amount during the 2000s, as it compensated the groundwater pumping. This study clearly revealed the processes of groundwater impact caused by excessive groundwater pumping using a combination of hydrogeochemical methods and modeling.

     

Erosion potential assessment of watersheds through GIS<Emphasis Type="Bold">-</Emphasis>based hypsometric analysis: a case study of Kurram Tangi Dam

Sediment discharge due to soil and rock erosion within the watersheds is the major cause of siltation in water reservoirs. Siltation in reservoirs reduces the capacity for power production, irrigation water supply, and other domestic purposes. Hypsometric analysis has widely been used to identifying the geomorphic development stages (stabilized, equilibrium, and un-stable) to assess the erosion proneness of watersheds. In this study, watershed of Kurram Tangi Dam and its four sub-watersheds (SWs) were considered to determine their sediment discharge capacity through hypsometric analysis. The boundaries of watershed and sub-watersheds were delineated from Digital Elevation Model (DEM). The hypsometric parameters i.e., hypsometric integral (HI) and curves were generated using Geographic Information System (GIS) techniques. The HI values of SW-1 (0.41) and SW-2 (0.36) indicated that these two SWs were relatively more prone to erosion and contributed higher sediment discharge in Dam siltation. The results were validated through sampling the main drainage channel (Kurram River) to determine the sediment concentration at 12 sites during summer, winter, and spring seasons. Comparison of HI and sediment concentration of SWs presented high correlation (R²?=?0.87). The results emphasized the effective watershed management, extensive afforestation, and construction of silt-control structures at appropriate locations in sub-watersheds. This will ultimately maintain the water and power generation capacity as well as extending the life span of the Dam.     

Using large‐scale climatic patterns for improving long lead time streamflow forecasts for Gunnison and San Juan River Basins

In a water‐stressed region, such as the western United States, it is essential to have long lead times for streamflow forecasts used in reservoir operations and water resources management. Current water supply forecasts provide a 3‐month to 6‐month lead time, depending on the time of year. However, there is a growing demand from stakeholders to have forecasts that run lead times of 1 year or more. In this study, a data‐driven model, the support vector machine (SVM) based on the statistical learning theory, was used to predict annual streamflow volume with a 1‐year lead time. Annual average oceanic–atmospheric indices consisting of the Pacific decadal oscillation, North Atlantic oscillation (NAO), Atlantic multidecadal oscillation, El Niño southern oscillation (ENSO), and a new sea surface temperature (SST) data set for the ‘Hondo’ region for the period of 1906–2006 were used to generate annual streamflow volumes for multiple sites in the Gunnison River Basin and San Juan River Basin, both located in the Upper Colorado River Basin. Based on the performance measures, the model showed very good forecasts, and the forecasts were in good agreement with measured streamflow volumes. Inclusion of SST information from the Hondo region improved the model's forecasting ability; in addition, the combination of NAO and Hondo region SST data resulted in the best streamflow forecasts for a 1‐year lead time. The results of the SVM model were found to be better than the feed‐forward, back propagation artificial neural network and multiple linear regression. The results from this study have the potential of providing useful information for the planning and management of water resources within these basins. Copyright © 2012 John Wiley & Sons, Ltd.     

PALEOMAGNETIC STUDY OF IGNEOUS ROCKS OF GUPIS—SHAMRAN AREA,KOHISTAN ARC, PAKISTAN,NW HIMALAYA

Kohistan Sequence has been considered as island arc formed during the subduction of oceanic lithosphere at the leading edge of northward moving Indian continent.. Sedimentary sequences indicate that formation of the intra\|oceanic Kohistan arc began in early Cretaceous time. The isotopic data demonstrate the involvement of enriched, DUPAL type mantle, suggesting that Kohistan arc was formed at or south of the present equator (Khan et al., 1997). The Intra oceanic phase of Kohistan lasted until sometime between 102 and 85 Ma, when Kohistan collided with Asia. From this time until collision with India about 50 Ma ago, Kohistan existed as Andean\|type margin. This paleomagnetic study is from the volcanic and plutonic rocks exposed in Gupis\|Shamran area (west of Gilgit) in northern part of the Kohistan arc. According to geochronological data these rocks were formed 61～55Ma ago (Treloar et al., 1989), when Kohistan was existing as Andean\|type margin. Seven to nine samples were collected from nine sites of Shamran volcanics (58±1)Ma and from five sites of Pingal, Gupis, and Yasin plutons (Ar\|Ar hornblende ages ranges from 61～52Ma). On the basis of one Rb\|Sr age of (59±2)Ma from these plutons, the above\|mentioned Ar/Ar ages may be regarded as reasonable intrusion ages of these plutons (Searle, 1991).     

A new method of snowmelt sampling for water stable isotopes

We modified a passive capillary sampler (PCS) to collect snowmelt water for isotopic analysis. Past applications of PCSs have been to sample soil water, but the novel aspect of this study was the placement of the PCSs at the ground‐snowpack interface to collect snowmelt. We deployed arrays of PCSs at 11 sites in ten partner countries on five continents representing a range of climate and snow cover worldwide. The PCS reliably collected snowmelt at all sites and caused negligible evaporative fractionation effects in the samples. PCS is low‐cost, easy to install, and collects a representative integrated snowmelt sample throughout the melt season or at the melt event scale. Unlike snow cores, the PCS collects the water that would actually infiltrate the soil; thus, its isotopic composition is appropriate to use for tracing snowmelt water through the hydrologic cycle. The purpose of this Briefing is to show the potential advantages of PCSs and recommend guidelines for constructing and installing them based on our preliminary results from two snowmelt seasons. Copyright © 2014 John Wiley & Sons, Ltd.     

Microwave solar limb brightening

Previous models of microwave limb brightening have omitted the alignment of spicules along supergranule boundaries, have neglected the high temperature sheath around spicules, and have assumed an interspicular medium which was averaged over chromospheric network and non-network regions. We present a model which includes these factors. By constraining the model to conform to results from earlier UV and optical studies we are effectively left with two free parameters: the temperature at the core of the spicules, T _core, and (at solar minimum), the interspicular chromospheric network density model of the lower transition zone. The absence of limb brightening at the short millimeter wavelengths implies T _core 6000 k. Differences between the model and certain deconvolved observations near 9 mm are expected as a consequence of an extension of emission beyond the optical limb, predicted by the model, which affects the accuracy of the deconvolution technique. Unlike models which assume homogeneous spicules in a random distribution, ours does not require an abnormally high spicule area.     

Application of newly developed ensemble machine learning models for daily suspended sediment load prediction and related uncertainty analysis

ABSTRACT

Ensemble machine learning models have been widely used in hydro-systems modeling as robust prediction tools that combine multiple decision trees. In this study, three newly developed ensemble machine learning models, namely gradient boost regression (GBR), AdaBoost regression (ABR) and random forest regression (RFR) are proposed for prediction of suspended sediment load (SSL), and their prediction performance and related uncertainty are assessed. The SSL of the Mississippi River, which is one of the major world rivers and is significantly affected by sedimentation, is predicted based on daily values of river discharge (Q) and suspended sediment concentration (SSC). Based on performance metrics and visualization, the RFR model shows a slight lead in prediction performance. The uncertainty analysis also indicates that the input variable combination has more impact on the obtained predictions than the model structure selection.